• Journal of Microbiology
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• v.33 no.2
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• pp.95-102
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• 1995

A probability identification matrix of acidophilic Streptomyces was constructed. The phenetic data of the strains were derived from numerical classification described by Seong et al. The minimum number of diagnostic characters was determined using computer programs for calculation of different separation indices. The resulting matrix consisted of 25 clusters versus 53 characters. Theoretical evaluation of this matrix was achieved by estimating the chuster overlap and the identification scores for the Hypothetical Median Organisms (HMO) and for the representatives of each cluster. Cluster overlap was found to be relatively small. Identification scores for the HMO and the randomly selected representatives of each cluster were satisfactory. The matrix was assessed practically by applying the matrix to the identification of unknown isolates. Of the unknown isolates, 71.9% were clearly identified to one of eight clusters. The numerical classification data was also used to design a selective isolation medium for antibiotic-producing organisms. Four chemical substances including 2 antibiotics were determined by the DLACHAR program as diagnostic for the isolation of target organisms which have antimicrobial activity against Micrococcus luteus. It was possible to detect the increased rate of selective isolation on the synthesized medium. Theresults show that the numerical phenetic data can be applied to a variety of purposes, such as construction of identification matrix and selective isolation medium for acidophilic antinomycetes.

• Structural Engineering and Mechanics
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• v.57 no.1
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• pp.21-43
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• 2016

A conditional probability based approach known as Particle Filter Method (PFM) is a powerful tool for system parameter identification. In this paper, PFM has been applied to identify the vehicle parameters based on response statistics of the bridge. The flexibility of vehicle model has been considered in the formulation of bridge-vehicle interaction dynamics. The random unevenness of bridge has been idealized as non homogeneous random process in space. The simulated response has been contaminated with artificial noise to reflect the field condition. The performance of the identification system has been examined for various measurement location, vehicle velocity, bridge surface roughness factor, noise level and assumption of prior probability density. Identified vehicle parameters are found reasonably accurate and reconstructed interactive force time history with identified parameters closely matches with the simulated results. The study also reveals that crude assumption of prior probability density function does not end up with an incorrect estimate of parameters except requiring longer time for the iterative process to converge.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.599-608
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• 2007

This study was conducted to establish an individual identification system in Hanwoo cattle. Samples of 33 Hanwoo individuals from Korean elite sire families were used. Thirteen major microsatellite markers were selected from alleles amplified, their frequencies, H(Heterozygosity) and PIC(Polymorphism Information Content) with Hardy-Weinberg equilibrium. Next, in order to evaluate the power of the markers selected on the individual animal identification, MP(Match probability) and R(Relatedness coefficient) with the percentage of animal incorrectly identified were computed. Finally nine microsatellite markers were selected and discussed.

• Phonetics and Speech Sciences
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• v.5 no.1
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• pp.91-98
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• 2013

This paper investigated Korean prosody as it relates to graded internal structure in an identification function. Within Korean prosody, variants regarded as dialectal variations can appear as different prosodic scales, which contain the range of within-category variations. The current experiment was intended to show how the prosodic scale corresponding to the range of within-category differences relates to f0 contours for speakers of two Korean dialects, North Kyungsang and South Cholla. In an identification task, participants responded by selecting an item from two answer choices. The probability of choosing the correct response from the two choices was computed by a logistic regression analysis using intercepts and slopes. That is, the correct response between two choices was used to show a linear line with an s-shape presentation. In this paper, to investigate the graded internal structure of labeling, 25%, 50%, and 75% of predicted probability were assessed. Listeners from North Kyungsang showed progressive variations, whereas listeners from South Cholla revealed random patterns in the internal structure of the identification function. In this paper, the results were plotted using scatterplot graphs, applying the range of within-category variation and predicted probability obtained from the logistic regression analyses. The scatterplot graphs showed the different degree of the responses for f0 scales (i.e., variations within categories). The results demonstrate that the gradient structures of native pitch accent users become more progressive in response to f0 scales.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.6
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• pp.299-311
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• 2008

The Radio Frequency IDentification (RFID) system is a contactless automatic identification system, which comprises readers and tags. In RFID systems, a reader collision occurs when there is interference in communication between one reader and the tags, due to the signals from other readers. The reader collision problem is considered as the fundamental problem affecting high density RFID reader installations. In this paper, we analyze the existing reader anti-collision algorithms. We also propose a pulse protocol-based reader anti-collision algorithm using slot occupied probability (SOP). The implementation of this improvement is simple, yet it effectively mitigates most reader collisions in dense reader mode, as shown in our simulation. That is, the proposed algorithm reduces the identification time, and increasesthe system throughput and system efficiency compared with the conventional reader anti-collision algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.18-21
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• 1995

In this paper we describe a new method for multimodal function optimization using genetic algorithms(GAs). We propose adaptation rules for GA parameters such as population size, crossover probability and mutation probability. In the self organizing genetic algorithm(SOGA), SOGA parameters change according to the adaptation rules. Thus, we do not have to set the parameters manually. We discuss about SOGA and those of other approaches for adapting operator probabilities in GAs. The validity of the proposed algorithm will be verified in a simulation example of system identification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1984-1989
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• 1998

Convergence properties of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion is presented.In particular, the performnce of the algorithmis examined and compared with least mena square (LMS) algorithm for several different probability densities of the measurement noisein a system identification mode. It is observedthat the LMAT algorithm outperforms the LMS algorithm for most of the noise probability densities, except for the case of the exponentially distributed noise.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.27-33
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• 2006

In this paper, an effective method for identifying influential main effects and interactions in the 2-level factorial designs is suggested by exploiting the resolution V designs developed by Kim(1992). For analysis of such designs, we employ the Bayesian approach for easy and clear identification of influential effects in the half normal probability plot.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.987-996
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• 2008

In this paper, the conventional anti-collision algorithms, such as Channel Monitoring algorithm and Pulse Protocol algorithm are analyzed. To decrease tag identification time, and increase system throughput and efficiency, we propose a new reader anti-collision algorithm, Pulse Protocol-based Hybrid Reader Anti-collision Algorithm, using Slot-occupied Probability under dense reader environment. The proposed algorithm uses Slot-occupied Probability to improve the performance of Pulse Protocol Algorithm. That is, A reader checks Slot-occupied Probability after generating random backoff time. If Slot-occupied Probability is greater than 0, it uses another new random backoff time to avoid reader collision. We also compare the performance of the proposed algorithm with those of Channel Monitoring and Pulse Protocol algorithms in respect of identification time system throughput, and system efficiency. Simulation results show that the proposed algorithm has an increment of 5% of identification time and system throughput as increasing the number of readers.

• 전기의세계
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• v.29 no.11
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• pp.742-750
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• 1980

The problem of nonlinear time-invariant system identification by estimation of Wiener kernels is studied for discrete time systems with inputs having symmetric probability distributions. G-functionals are constructed. It is further shown that under idealized conditions, these seemingly different techniques yield the same results. The results of identification of asimulated second degree system is presented.